Staff Software Engineer, AI Compute Infrastructure

Quick Facts

Salary Range: $209,100-$282,900 per year. Relocation package (including visa sponsorship support) is available for candidates who require it. Hybrid working supports both in-person collaboration and flexibility based on team needs and role constraints.

Description

As an engineer on the AI Compute Infra team, you will design, build, and operate large-scale infrastructure for AI training, fine-tuning, evaluation, and inference. You will work across Kubernetes clusters, accelerator enablement, workload scheduling, high-performance networking, storage, and capacity management, partnering with AI researchers and engineers to improve reliability, performance, scalability, and developer productivity.

Responsibilities

• Build and operate Kubernetes clusters while improving workload scheduling, topology-aware placement, capacity use, and recovery.

• Enable new CPU and GPU systems by integrating and validating drivers, networking, storage, monitoring, and health checks.

• Investigate performance and reliability issues across applications, cloud infrastructure, clusters, and hardware, then turn findings into lasting improvements.

• Partner with AI teams to understand their workloads and automate cluster provisioning, upgrades, monitoring, and maintenance around their needs.

Requirements

• 5+ years of experience building or operating cloud, compute, HPC, or distributed infrastructure in a production environment.
• Programming experience in Go, Python, or another systems language, with an interest in developing reliable infrastructure software.
• Practical knowledge of Kubernetes, containers, Linux, networking, and storage.
• Experience supporting GPU, accelerator, or distributed machine-learning workloads.
• Ability to troubleshoot complex systems and communicate clearly with engineers from different technical backgrounds.

Benefits

• Relocation package including visa sponsorship support for candidates who require it.

• Driven group focused on world-class AI compute infrastructure and smooth operations.

• Hybrid working model with team-determined patterns.

• Equal opportunity employer commitment and support for reasonable accommodations during the application and interview process.